| PharmaSUG CN |
2026 |
Interactive Clinical Plot Gallery with Cross-Plot Subject Linking in R Shiny |
You (Lea) Lyu |
source |
10 |
| PharmaSUG |
2026 |
Advanced SAS Graph Template Language (GTL) with Practical Examples from Oncology Trials |
Ceng Qian, Xu Wen, Wei Lei, Ling Han |
source |
15 |
| PharmaSUG |
2025 |
Addressing early challenges in RWD data standardization for analysis and reporting of RWE studies |
Xingshu Zhu, Li Ma, Bo Zheng |
source |
9 |
| PharmaSUG |
2025 |
Efficacy Endpoints Related to CNS in Oncology Studies within ADaM |
Lihui Deng, Kylie Fan |
source |
6 |
| PharmaSUG |
2025 |
Roadmap to Efficacy Analysis for Early Phase Oncology studies |
Dhruv Bansal, Christiana Hawn, Chris Kelly |
source |
23 |
| PHUSE US |
2025 |
Enhancing Clinical Trial Data Queries with LLMs and Neo4j: A Flexible Framework for ADaM Dataset Management |
Jaime Yan |
source presentation source |
28 |
| PHUSE EU |
2024 |
Insights of Using {admiralonco} at BMS: Facilitating Oncology Efficacy ADaM Datasets |
Yirong Cao, Yi Yan |
source presentation source |
10 |
| PharmaSUG CN |
2024 |
Best Overall Response (BOR) Confirmation in Oncology Clinical Trials: Insights from RECIST 1.1 |
Jihai Li |
source |
15 |
| PharmaSUG |
2024 |
ADaM Design for Prostate Cancer Efficacy Endpoints Based on PCWG3 |
Lihui Deng, Kylie Fan, Jia Li |
source |
10 |
| PHUSE US |
2024 |
A Step-by-Step Programming Approach to Summarize Best Response in Patients with Multiple Myeloma Who Had Positive and Negative |
MRD Test |
source presentation source |
8 |
| PHUSE US |
2024 |
Confirmation and Cancellation - Best Strategies for Data Collection and Handling within Solid Tumor Studies Using RECIST 1.1 and iRECIST Guidelines |
Sherry Ye, Abraham Yeh |
source presentation source |
10 |
| WUSS |
2023 |
Waterfall vis a vis Spider plots: Complex oncology efficacy endpoint made simpler. |
Yoganand Budumuru |
source |
21 |
| PharmaSUG |
2023 |
ADaM Design and Programming Standardization for Oncology Efficacy Endpoints Based on RECIST 1.1 |
Ellen (Zihui) Lin, Matt Ness, Yinghui Wang |
source |
9 |
| PharmaSUG |
2023 |
Admiralonco - The Cross-Company R Package for Oncology Admirers |
Neharika Sharma, Matthew Marino |
source |
25 |
| PharmaSUG |
2023 |
Confirmation of Best Overall Tumor Response in Oncology Clinical Trials per RECIST 1.1 |
Danyang Bing |
source |
3 |
| PharmaSUG |
2023 |
Leverage and Enhance CDISC TAUGs to Build More Traceability for and Streamline Development of Efficacy ADaM in Oncology Studies |
Xiangchen (Bob) Cui |
source |
29 |
| PharmaSUG |
2023 |
Sound SDTM, Sound ADaM - Orchestrating SDTM and ADaM Harmonization |
Nancy Brucken, David Neubauer, Soumya Rajesh |
source |
8 |
| PharmaSUG |
2022 |
A Dynamic Data Visualization Report for Efficacy Endpoints of Early Oncology Study |
Hong (Lily) Zhang, Yixin Ren, Huei-Ling Chen |
source |
10 |
| PHUSE EU |
2021 |
How Has the Immunotherapy Era Changed Response Criteria? [presentation] |
Anna Amosova |
source video |
30 |
| PharmaSUG |
2020 |
Butterfly Plot for Comparing Two Treatment Responses |
Raghava Pamulapati |
source |
13 |
| PharmaSUG |
2020 |
Calculation of Cochran-Mantel-Haenszel Statistics for Objective Response and Clinical Benefit Rates and the Effects of Stratification Factors |
Girish Kankipati, Chia-Ling (Ally) Wu |
source |
8 |
| PharmaSUG |
2020 |
Implementation of Immune Response Evaluation Criteria in Solid Tumors (iRECIST) in Efficacy Analysis of Oncology Studies |
Weiwei Guo |
source |
6 |
| PharmaSUG |
2020 |
Oncology Graphs-Creation (Using SAS and R), Interpretation and QA |
Taniya Muliyil |
source |
10 |
| PharmaSUG |
2020 |
Simplifying the Derivation of Best Overall Response per RECIST 1.1 and iRECIST in Solid Tumor Clinical Studies |
Xiangchen (Bob) Cui, Sri Pavan Vemuri |
source |
24 |
| SESUG |
2019 |
Cutting Out the Middle Man - Bypassing ADaM to Calculate Tumor Response Inputs using RECIST 1.1 Guidelines and Collected Data in SDTM Format |
Response Inputs |
source |
6 |
| PharmaSUG |
2019 |
Fine-tuning your swimmer plot: another example from oncology |
Steve Almond |
source |
25 |
| PharmaSUG |
2019 |
Useful SAS techniques in Efficacy Analysis for Oncology studies |
Joy Zeng |
source |
21 |
| PHUSE US |
2019 |
Efficacy Endpoint Visualization of Investigational Products for Cancer Patients Using R Shiny |
Beverly Martinez, Mukul K Mittal |
source presentation source |
12 |
| PHUSE EU |
2018 |
Step-by-step Guide to Efficacy Analysis in Solid Tumors Oncology Clinical Trials |
Anastasiia Tiurdo |
source presentation source |
11 |
| PharmaSUG |
2018 |
Derivations of Response Status from SDTM Domains using RECIST 1.1 |
Christine S Teng, Lei Pang |
source |
10 |
| PharmaSUG |
2018 |
Leveraging Standards for Effective Visualization of Early Efficacy in Clinical Trial Oncology Studies |
Kelci J. Miclaus, Lili Li |
source |
12 |
| PharmaSUG |
2017 |
SAS Macro for Derivation of Best Overall Response per RECIST v. 1.1 |
Bob Zhong, Jiangfan Li, Hong Xie, Peter De Porre, Kenneth Maahs, Kyounghwa Bae |
source |
9 |
| MWSUG |
2016 |
Defensive Coding by Example: Kick the Tires, Pump the Brakes, Check Your Blind Spots, and Merge Ahead! |
Nancy Brucken, Donna E. Levy |
|
16 |
| PharmaSUG |
2016 |
Deconstructing ADRS: Tumor Response Analysis Data Set |
Steve Almond |
source |
11 |
| PharmaSUG |
2016 |
Programming Support for Exposure-Response Analysis in Oncology Drug Development |
Peter Lu, Hong Yan |
source |
8 |
| SGF |
2016 |
Graphical Results in Clinical Oncology Studies |
Nora Ruel |
source |
14 |
| WUSS |
2015 |
Graphical Results in Clinical Studies A focus on graphics used in oncology |
Nora Ruel, Paul Frankel |
source |
12 |
| PharmaSUG |
2015 |
Defensive Coding by Example: Kick the Tires, Pump the Breaks, Check Your Blind Spots, and Merge Ahead! |
Nancy Brucken, Donna E. Levy |
source |
16 |
| PharmaSUG |
2015 |
Two different use cases to obtain best responses using RECIST 1.1: SDTM and ADaM |
Kevin Lee, Vikash Jain |
source |
17 |
| SGF |
2015 |
Defensive Coding by Example: Kick the Tires, Pump the Breaks, Check Your Blind Spots, and Merge Ahead! |
Donna E. Levy, Nancy Brucken |
source |
17 |
| PHUSE EU |
2013 |
Overcoming Difficulties in Implementing RECIST Criteria |
Gerlind Ruhnke |
source presentation source |
6 |
| PHUSE EU |
2012 |
Study Protocol Flexibility vs Programming Standard Rigidity |
Samia Kabi |
source poster source |
7 |
| MWSUG |
2011 |
Objective tumor response and RECIST criteria in cancer clinical trials |
Jian Yu |
|
6 |
| PHUSE EU |
2010 |
Theory U-Social Technology for Innovation |
Colin Brown |
source |
5 |
| PharmaSUG |
2010 |
Application of Modular Programming in Clinical Trial Environment |
Mirjana Stojanovic |
|
8 |
| SESUG |
2009 |
A Modular Approach to Develop Complex Data Errors Checking Program in Clinical Trial Environment |
Mirjana Stojanovic, Laura E. Archer |
source |
7 |
| MWSUG |
2008 |
Creating Macros for Survival Data in Oncology Study |
Jagannath Ghosh |
|
8 |
| SUGI |
2005 |
Standardization through Macros: The Possibilities of Using Indirect Referencing to Macro Variables |
Britta Kelsey |
source |
8 |
| SEUGI |
2001 |
Sales Force Management Through Intranet [presentation] |
Anna Surova, Jan Maly, Jaroslav Kafka |
source |
21 |
| SEUGI |
2000 |
Implementing a Balanced Scorecard on top of SAP/RE-FI Using SAS CFO Vision as Interface [presentation] |
Ida R. Carapelle, Sophie De Baets |
source |
42 |
| SEUGI |
1995 |
The PIL: An Alternative Approach to Forecasting System Load |
Peter Van Gils |
source |
22 |
| SEUGI |
1993 |
BAVIS - the Badenia EIS |
Christian Horning |
source |
8 |